numdifftools 0.9.10

'Solves automatic numerical differentiation problems in one or more variables.'

Suite of tools written in _Python to solve automatic numerical differentiation problems in one or more variables. Finite differences are used in an adaptive manner, coupled with a Richardson extrapolation methodology to provide a maximally accurate result. The user can configure many options like; changing the order of the method or the extrapolation, even allowing the user to specify whether complex-step, central, forward or backward differences are used.

The methods provided are:

• Derivative: Compute the derivatives of order 1 through 10 on any scalar function.

• Gradient: Compute the gradient vector of a scalar function of one or more variables.

• Jacobian: Compute the Jacobian matrix of a vector valued function of one or more variables.

• Hessian: Compute the Hessian matrix of all 2nd partial derivatives of a scalar function of one or more variables.

• Hessdiag: Compute only the diagonal elements of the Hessian matrix

All of these methods also produce error estimates on the result.

The documentation for numdifftools is available here http://numdifftools.readthedocs.org/

Download the toolbox here: http://pypi.python.org/pypi/Numdifftools

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News

2015

August 20

New release of Numdifftools 0.9.2.

2014

December 18

New release of Numdifftools 0.7.7.

December 17

New release of Numdifftools 0.7.3.

February 8

New release of Numdifftools 0.6.0. :

January 10

New release of Numdifftools 0.5.0.

2012

May 5

New release of Numdifftools 0.4.0.

2011

May 19

New release of Numdifftools 0.3.5.

Feb 24

New release of Numdifftools 0.3.4.

2009

May 20

New beta release of Numdifftools 0.3.1.